Impaired response to COVID-19 vaccination is of particular concern in immunosuppressed patients. To determine the best vaccination strategy for this vulnerable group we performed a single center, 1:1 randomized blinded clinical trial. Patients who failed to seroconvert upon two mRNA vaccinations (BNT162b2 or mRNA-1273) are randomized to receive either a third dose of the same mRNA or the vector vaccine ChAdOx1 nCoV-19. Primary endpoint is the difference in SARS-CoV-2 spike antibody seroconversion rate between vector and mRNA vaccinated patients four weeks after the third dose. Secondary outcomes include cellular immune responses. Seroconversion rates at week four are significantly higher in the mRNA (homologous vaccination, 15/24, 63%) as compared to the vector vaccine group (heterologous vaccination, 4/22, 18%). SARS-CoV-2-specific T-cell responses are reduced but could be increased after a third dose of either vector or mRNA vaccine. In a multivariable logistic regression analysis, patient age and vaccine type are associated with seroconversion. No serious adverse event is attributed to COVID-19 booster vaccination. Efficacy and safety data underline the importance of a booster vaccination and support the use of a homologous mRNA booster vaccination in immunosuppressed patients.Trial registration: EudraCT No.: 2021-002693-10.

Background: In the context of the COVID-19 pandemic, numerous new serological test systems for the detection of anti-SARS-CoV-2 antibodies have become available quickly. However, the clinical performance of many of them is still insufficiently described. Therefore we compared three commercial, CE-marked, SARS-CoV-2 antibody assays side by side. Methods: We included a total of 1,154 specimens from pre-COVID-19 times and 65 samples from COVID-19 patients (≥14 days after symptom onset) to evaluate the test performance of SARS-CoV-2 serological assays by Abbott, Roche, and DiaSorin. Results: All three assays presented with high specificities: 99.2% (98.6-99.7) for Abbott, 99.7% (99.2-100.0) for Roche, and 98.3% (97.3-98.9) for DiaSorin. In contrast to the manufacturers’ specifications, sensitivities only ranged from 83.1% to 89.2%. Although the three methods were in good agreement (Cohen’s Kappa 0.71-0.87), McNemar’s test revealed significant differences between results obtained from Roche and DiaSorin. However, at low seroprevalences, the minor differences in specificity resulted in profound discrepancies of positive predictability at 1% seroprevalence: 52.3% (36.2-67.9), 77.6% (52.8-91.5), and 32.6% (23.6-43.1) for Abbott, Roche, and DiaSorin, respectively. Conclusion: We find diagnostically relevant differences in specificities for the anti-SARS-CoV-2 antibody assays by Abbott, Roche, and DiaSorin that have a significant impact on the positive predictability of these tests.

For the identification of antigenic protein biomarkers for rheumatoid arthritis (RA), we conducted IgG profiling on high density protein microarrays. Plasma IgG of 96 human samples (healthy controls, osteoarthritis, seropositive and seronegative RA, n = 24 each) and time-series plasma of a pristane-induced arthritis (PIA) rat model (n = 24 total) were probed on AIT’s 16k protein microarray. To investigate the analogy of underlying disease pathways, differential reactivity analysis was conducted. A total of n = 602 differentially reactive antigens (DIRAGs) at a significance cutoff of p < 0.05 were identified between seropositive and seronegative RA for the human samples. Correlation with the clinical disease activity index revealed an inverse correlation of antibodies against self-proteins found in pathways relevant for antigen presentation and immune regulation. The PIA model showed n = 1291 significant DIRAGs within acute disease. Significant DIRAGs for (I) seropositive, (II) seronegative and (III) PIA were subjected to the Reactome pathway browser which also revealed pathways relevant for antigen presentation and immune regulation; of these, seven overlapping pathways had high significance. We therefore conclude that the PIA model reflects the biological similarities of the disease pathogenesis. Our data show that protein array analysis can elucidate biological differences and pathways relevant in disease as well be a useful additional layer of omics information.

Antibody tests are essential tools to investigate humoral immunity following SARS-CoV-2 infection. While first-generation antibody tests have primarily provided qualitative results with low specificity, accurate seroprevalence studies and tracking of antibody levels over time require highly specific, sensitive and quantitative test setups. Here, we describe two quantitative ELISA antibody tests based on the SARS-CoV-2 spike receptor-binding domain and the nucleocapsid protein. Comparative expression in bacterial, insect, mammalian and plant-based platforms enabled the identification of new antigen designs with superior quality and high suitability as diagnostic reagents. Both tests scored excellently in clinical validations with multi-centric specificity and sensitivity cohorts and showed unprecedented correlation with SARS-CoV-2 neutralization titers. Orthogonal testing increased assay specificity to 99.8%, thereby enabling robust serodiagnosis in low-prevalence settings. The inclusion of a calibrator permits accurate quantitative monitoring of antibody concentrations in samples collected at different time points during the acute and convalescent phase of COVID-19.

Background Serological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems is often poor, leaving room for false positive and false negative results. However, conventional methods used to increase specificity decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the "Sensitivity Improved Two-Test" or "SIT ² " algorithm. Methods SIT ² involves confirmatory re-testing of samples with results falling in a predefined retesting-zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT ² to single tests and orthogonal testing (OTA) in an Austrian cohort (1,117 negative, 64 post-COVID positive samples) and validated the algorithm in an independent British cohort (976 negatives, 536 positives). Results The specificity of SIT ² was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT ² when compared to single tests or OTA. SIT ² allowed correct identification of infected individuals even when a live virus neutralization assay could not detect antibodies. Compared to single testing or OTA, SIT ² significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence. Conclusion For SARS-CoV-2 serology, SIT ² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.